Seasonal dynamics of the depth and rate of anaerobic ...eprints.uni-kiel.de/235/1/s5.pdf · Seasonal dynamics of the depth and rate of anaerobic oxidation of methane in Aarhus Bay

Seasonal dynamics of the depth and rate of anaerobicoxidation of methane in Aarhus Bay (Denmark) sediments

by A W Dale12 D R Aguilera1 P Regnier1 H Fossing3N J Knab4 and B B Joslashrgensen45

ABSTRACTA reactive-transport model has been applied to investigate the dynamics of the sulfate-methane

transition zone (SMTZ) in nearshore sediments of Aarhus Bay (Denmark) The sediments areinfluenced by seasonal variations of temperature and particulate organic carbon (POC) depositionflux at the sediment-water interface Initially the model was calibrated at steady state using field datacollected at two sites (M1 and M5) in December 2004 and included a dynamic gas phase whichdetermines the depth of the SMTZ Simulations were then performed under transient conditions ofheat propagation in the porous medium which influenced the solubility of gaseous methane thediffusion of solutes as well as the kinetic and bioenergetic constraints on redox conditions in thesystem Results revealed important variations in local rates of anaerobic oxidation of methane(AOM) over a seasonal cycle due to temperature variation Seasonal perturbations in POCdepositional flux had no influence on AOM rates but did have a strong bearing on sulfate reductionrates in the surface layers of the simulations at both stations At M5 where the SMTZ was located63 cm below the sediment-water interface depth integrated AOM rates varied between 76 and178 nmol cm-2 d-1 At M1 where the deeper SMTZ (221 cm) experienced less thermal variationAOM rates varied relatively less (20 to 24 nmol cm-2 d-1) Furthermore local and depth-integratedAOM rates over the year did not show a simple response to bottom water temperature but exhibited ahysteresis-type behavior related to time lags in solute transport and heat propagation Overall thesolute concentration profiles were not very sensitive to the seasonal variability in rates or gastransport and the modeled vertical displacement of the SMTZ was limited to 1 cm at M1 and2ndash3 cm at M5 The results suggest that the significantly larger apparent displacement observed in thefield from repeated coring (80 cm and 16 cm at M1 and M5 respectively) must be attributed to otherfactors of which spatial heterogeneity in gas transport rate appears to be the most likely

1 Department of Earth Sciences ndash Geochemistry Utrecht University P O Box 80021 3508 TA UtrechtNetherlands

2 Corresponding author email dalegeouunl3 National Environmental Research Institute Department of Marine Ecology Vejlsoslashvej 25 8600 Silkeborg

Denmark4 MPI for Marine Microbiology Celsiusstr 1 D-18359 Bremen Germany5 Center for Geomicrobiology University of Aarhus Ny Munkegade Bldg 1540 DK-8000 Aringrhus C

Denmark

Journal of Marine Research 66 127ndash155 2008

127

101357002224008784815775

1 Introduction

Several detailed experimental studies have shown that organic matter mineralizationrates and microbial activity in both nearshore (eg Westrich and Berner 1988 Klump andMartens 1989) and deep-sea sedimentary environments (eg Soetaert et al 1996Moodley et al 2005) can be influenced by seasonal changes in temperature andorparticulate organic carbon (POC) flux to the sea floor Such seasonal variability at thesediment-water interface leads to concentration gradients of the primary oxidants of POCmineralization (eg O2 NO3

- Mn(IV) Fe(III) SO42-) which are not constant with time (Crill

and Martens 1987 Glud et al 2003 Koretsky et al 2005 Treude et al 2005) Themagnitude of this seasonal oscillation depends on the relative size of the perturbation at thesystem boundaries the rates of transport and reaction and thus on the quality of thesubstrate (Treude et al 2005 Burdige 2006) Additional complexities can be introducedby the substrate uptake response to temperature which is not necessarily the same for theentire microbial community (Weston and Joye 2005) Consequently modeling approacheshave proved useful to elucidate the seasonal variability observed in the redox biogeochem-istry of sediments (Klump and Martens 1989 Alperin et al 1994)

Aarhus Bay is a shallow embayment on the eastern Danish coast characterized by arelatively small yet notable seasonal change in the sediment depth distribution of oxidizedand reduced metabolites (eg Fe2 NH4

H2S) (Thamdrup et al 1994 Fossing et al2004) The quantitative significance of these seasonal changes for the sulfate reducing andmethanogenic zones has not yet been addressed although investigations elsewhere haverevealed seasonal variability resulting from significant changes in redox rates directly orindirectly coupled to organic matter decomposition (Crill and Martens 1987 Klump andMartens 1989) Sediment cores collected in Aarhus Bay and analyzed during theMETROL project (wwwmetrolorg) revealed that the subsurface sediments are methane-rich with a well-defined sulfate-methane transition zone (SMTZ) where sulfate andmethane simultaneously coexist In this SMTZ methane is oxidized anaerobically bymicroorganisms using sulfate as the terminal electron acceptor (Hoehler et al 1994Boetius et al 2000) Although anaerobic oxidation of methane (AOM) is a sluggishprocess it constitutes a globally effective sink against methane escape from marinesediments to the ocean and atmosphere (Reeburgh 1996) AOM is particularly relevant inthe sediments of Aarhus Bay because super-saturation of the pore water leads to theformation of methane bubbles which are detectable by ship-board seismic-acousticprofiling techniques (Laier and Jensen 2007) An investigation into the dynamics ofmethane and AOM over a seasonal cycle in an organic-rich nearshore environment such asAarhus Bay will thus provide additional constraints on the environmental factors regulat-ing the efficiency of the subsurface methane barrier

In this study a reaction-transport model (RTM) is applied to data from Aarhus Baysediments to investigate the role of seasonal bottom water temperature on substrateturnover rates with particular reference to sulfate reduction coupled to AOM and theSMTZ depth For the sake of completeness the variability in POC depositional flux is also

128 [66 1Journal of Marine Research

considered To help identify the effect of seasonal changes in bottom water temperaturethe heat equation is solved to simulate the spatial and temporal evolution of temperature inthe sediment This variable influences the biogeochemical reaction rates the rate of solutediffusion and the solubility of methane The reaction network employed is similar to thatdeveloped by Dale et al (2008) for sediments from a similar depositional environment inthe Skagerrak and focuses on sulfate reduction and methanogenesis which are ultimatelydriven by hydrolysis and fermentation of POC deposited at the sediment surface Howeverin addition to the transient effects the present model includes an explicit representation ofthe gaseous methane phase The gas concentration is dependent on the in situ methanesolubility the rate of gas transport through the sediment and ebullition and dissolution Themodel elucidates the quantitative role of temperature on the spatial and temporal distribu-tion of constituent concentrations and microbial reaction rates in the anoxic sediments ofAarhus Bay

2 Material and methods

a Site description and data acquisition

Aarhus Bay is a shallow semi-enclosed embayment situated on the transition betweenthe North Sea and Baltic Sea characterized by elevated primary production from spring tofall (Glud et al 2003) The sediments in the bay are 6ndash7 m thick Holocene mud deposits(10 ky BP Jensen and Laier 2003) which overlie brackish late glacial clay-silt and till(Laier and Jensen 2007) Free methane gas in the sediment is widespread where the mudthickness exceeds 4-5 m and the upper boundary of gas below the sea floor varies from50 cm to 400 cm depth (Laier and Jensen 2007)

Samples were collected during METROL (wwwmetrolorg) research cruises in AarhusBay Denmark on four occasions between March 2003 and December 2004 Two stationswere visited Station M1 located at position 56o0707N 10o2079E (15 m water depth) andStation M5 at 56o0620N 10o2747E (27 m water depth) This study presents data fromDecember 2004 (bottom water temperature 281 K) which exemplify the main geochemicalcharacteristics of the system Weekly time series data during 2004 revealed that bottomwater salinity undergoes a variation of 27 2 with no seasonal pattern (data not shown)Groundwater seepage was not observed at the study sites

Gravity cores of 3 m length were collected and sectioned in 10 cm depth intervals forbiogeochemical analyses Part of the surface sediment was lost during gravity coring andthe upper 50 cm of undisturbed surface sediment was in addition sampled with a smallerlsquoRumoHr Lotrsquo coring device The sulfate (SO4

2-) concentration profiles measured in the twosediment cores were superimposed and the loss of sediment was calculated with a 3 cmuncertainty in the thickness of sediment lost during gravity coring The data in this studyare plotted using this corrected composite depth

Methane (CH4) concentration was determined in a sediment sample of 3 cm3 Thesediment was sampled immediately after retrieval of the sediment core and transferred to a

2008] 129Dale et al Seasonal anaerobic oxidation of methane

20 ml serum vial with 6 ml demineralized water capped with a butyl rubber stoppercrimp-capped and vigorously shaken After gas equilibration the headspace was analyzedon a gas chromatograph (5890A Hewlett Packard) equipped with a packed stainless steelPorapak-Q column (6 ft 0125 in 80100 mesh Agilent Technology) and a flameionization detector Helium was used as a carrier gas at a flow rate of 30 ml min-1 and theCH4 peak appeared 065 minutes after injection of the headspace gas The area of theCH4-peak was calculated with an integrator (Hewlett Packard 3395)

Particulate organic carbon (POC) was determined on approximately 100 mg of driedsediment acidified with 1ndash2 drops of H2SO4 to degas carbonates as CO2 The acid-washedsample was then combusted in a CHN-analyzer (Roboprep CN Europe Scientific UK)during which POC was transferred to CO2 and measured by TCD-detection The POCcontent was calculated in mg C and expressed as percent dry sediment weight

Dissolved inorganic carbon (DIC) concentrations were measured by flow injection (Halland Aller 1992) on headspace-free sealed pore water samples stored at 10degC The sampleswere injected into a continuous flow of HCl solution (30 mM) and the CO2 diffused acrossa Teflon membrane into NaOH (10 mM) and measured by a conductivity detector (VWRscientific model 1054)

The SO42- concentration was measured in pore water squeezed from 20 cm3 sediment

with N2 through a 045 m cellulose acetate filter Pore water was collected into a 5 mlglass syringe and 1 ml was preserved 025 ml ZnCl2 (2 wv) for subsequent sulfateconcentration measurement Depending on the sulfate concentration the ZnCl2 preservedpore water sample was diluted up to 100 fold and filtered (045 m) before measurementConcentration determination was done by non-suppressed anion exchange chromatogra-phy (Waters 510 HPLC Pump Waters IC-Pak 50 x 46 mm anion exchange columnWaters 430 Conductivity detector) with an isophthalic acid eluant (1 mM pH 47 inmethanol 10 vv)

Sulfate reduction (SR) rates were determined by the 35SO42- tracer method in 10 cm long

sub-cores (26 mm ID) (Joslashrgensen 1978) sampled directly from the gravity core Immedi-ately after sub-sampling 10 l (400 kBq) carrier-free 35SO4

2- (Risoslash Isotope LaboratoryDenmark) was injected horizontally at 1 cm intervals into the sediment through silicone-stoppered ports The radio-labeled sub-cores were incubated for 8 ndash 16 hours at in situtemperature in the dark and terminated by preserving 2 cm sediment sections in 20 ZnAc(vv) The preserved sediment was vigorously shaken and frozen until distillation anddetermination of 35SO4

2- and 35S (in Chromium Reducible Sulfur CRS ieH2

35SFe35S35SoFe35S2) following the technique of Fossing and Joslashrgensen (1989)The SR rate was calculated from the fraction of reduced sulfur produced

SR

SO4

224

tinc106 nnol cm3 d1 (1)

where is the radioactivity of the reduced 35S per volume sediment is the radioactivity ofa blank sample (ie the carry over of 35SO4

2- analyzed as reduced 35S (Fossing et al 2000))


is the radioactivity of the sulfate per sediment volume after incubation [SO42-] is the

sulfate concentration (nmol cm-3) tinc is the incubation time in hours and 106 is anestimated isotopic fractionation factor

b Model set-up

i Coupled transport and reaction The model approach for M1 and M5 was divided intotwo parts (i) a steady state baseline simulation consisting of the model calibration to theDecember 2004 data and (ii) transient simulations to investigate the physical andgeomicrobial response to seasonal forcing at the sediment surface The reaction networkimplemented was similar to the one used by Dale et al (2008) for modeling anaerobicdiagenesis in Skagerrak sediments The model simulated the 700 cm of Holocene mudpresent at M1 and M5 and included six dissolved species (sulfate (SO4(aq)

2- ) methane(CH4(aq)) hydrogen (H2(aq)) acetate (CH3COO(aq)

- termed Ac hereafter) dissolved inor-ganic carbon (DIC) low molecular weight dissolved organic carbon (LMW-DOC) andthree types of solid POC species a labile (POCLAB) and refractory fraction (POCREF) and afraction of intermediate reactivity (POCMID) for M5 only One gaseous species (methanegas CH4(g)) was also considered Tables 1 and 2 present the reaction network and thecorresponding rate parameters respectively

The one-dimensional scalar mass-conservation equation (eg Berner 1980 Boudreau1997) was used to resolve the depth profiles of solutes (Eq 2a) solids (Eq 2b) and CH4(g)

(Eq 2c)

13CS

t

x 13DS DbCS

x 13vCS

x 13CS0 CS)13R (2a)

1 13CP

t

x 1 13Db

CP

x 1 13vCP

x 1 13R (2b)

13CH4g

t

x 13DCH4g DbCH4g

x 13vCH4g

x 13CH4g0 CH4g 13R

(2c)

where x (cm) is the vertical depth t (y) is time 13 (L pore water (L wet sediment)-1) is thedepth-dependent porosity CS (mol L-1) and CP (mol g-1) are the timendashdependent concen-trations of solutes and solids respectively CS0 (mol L-1) and CH4(g)0 (mol L-1) are thesolute and CH4(g) concentration at the top of the core DS (cm2 y-1) is the tortuosity-corrected molecular diffusion coefficient Db (cm2 y-1) is the bioturbation coefficientv (cm y-1) is the sediment accumulation rate (y-1) is the bioirrigation coefficient and R isthe sum of the rate of concentration change due to reactions Further details of the depthdependency of Db and are summarized in Table 3

CH4(g) was transported through the sediment using an apparent diffusion coefficientDCH4(g) (Table 3) This was used as a model fit parameter for the depth of the SMTZ since


Table 1 Reaction network and depth-integrated turnover rates (nmol cm2 d1) of the substrates (inbold) for the steady-state baseline simulations (upper in bold italic) and the seasonal range(below) rounded to the nearest integer Reactions are written for the transfer of 1 mole of electronswhere DIC POC and LMW-DOC are defined as bicarbonate ion (HCO3(aq)

) carbohydrate(CH2O(s)) and glucose (C6H12O6(aq)) respectively for mass balance and Gibbs energy calcula-tions

ReactionRate M1 baseline

min3 maxRate M5 baseline

min3 max

R1 HYDROLYSIS of POC to LMW-DOC 1233 332CH2O(s)3 1frasl6 C6H12O6(aq) 11303 1262 2753 427

R2 FERMENTATION of LMW-DOC 194 581frasl24 C6H12O6(aq) 1frasl6 H2O(1)3 1frasl12 CH3COO(aq)

1frasl6 H2(aq) 1frasl6 H(aq)

1frasl12 HCO3(aq)

1783 198 483 75

R3 SULFATE REDUCTION with H2 (hySR) 963 7091frasl2 H2(aq) 1frasl8 SO4(aq)

2 1frasl8 H(aq) 3 1frasl8 HS(aq)

1frasl2 H2O(1)

9093 1010 5153 985

R4 SULFATE REDUCTION with Ac (acSR) 362 1081frasl8 CH3COO(aq)

1frasl8 SO4(aq)2 3 1frasl8 HS(aq)

1frasl4 HCO3(aq)

3393 378 763 146

R5 METHANOGENESIS with H2 (hyME) 0 01frasl2 H2(aq) 1frasl8 HCO3(aq)

1frasl8 H(aq) 3 1frasl8 CH4(aq)

3frasl8 H2O(1)

R6 METHANOGENESIS with Ac (acME) 3 11frasl8 CH3COO(aq)

1frasl8 H2O(1)3 1frasl8 CH4(aq) 1frasl8 HCO3(aq)

23 3 03 1

R7 ANAEROBIC OXIDATION OF METHANE (AOM)dagger 24 1111frasl8 CH4(aq) 3frasl8 H2O(1)3 1frasl2 H2(aq) 1frasl8 HCO3(aq)

1frasl8 H(aq)

203 24 763 178

R8 ACETOGENESIS (acet) 0 01frasl2 H2(aq) 1frasl4 HCO3(aq)

1frasl8 H(aq) 3

1frasl8 CH3COO(aq) 1frasl2 H2O(1)

R9 ACETOTROPHY (actr) 24 81frasl8 CH3COO(aq)

1frasl2 H2O(1)3 1frasl2 H2(aq) 1frasl4 HCO3(aq)

1frasl8 H(aq)

243 27 53 11

Gas transfer processes

R10 METHANE GAS FORMATION 0 0CH4(aq)3 CH4(g) 03 105 03 662

R11 METHANE GAS DISSOLUTION 21 215CH4(g)3 CH4(aq) 193 110 1973 655

daggerAOM is assumed to be the reverse of bicarbonate methanogenesis (R5) (Hoehler et al 1994) butsee discussion by Nauhaus et al (2005)


Table 2 Biogeochemical parameters used to describe the rate of substrate uptake (Eq 6) at M1 andM5 Maximum substrate uptake rates (vmax) are calculated for a temperature of 27815 K (Dale etal 2006) and depend on T according to the function f(T) in Eq 5

Parameter DescriptionBaseline value

(M1M5) Units

khyLAB Hydrolysis rate of POCLAB 022012 y1

khyMID Hydrolysis rate of POCMID mdash00035 y1

khyREF Hydrolysis rate of POCREF 0 y1

Q10 Temperature dependence of vmax 38 or 20a mdashKSO4 Kinetic constant for SO4

2 uptake 10 103 MKH2-hySR Kinetic constant for H2 for hySR 10 108 MKAc-acSR Kinetic constant for Ac for acSR 10 104 MKH2-hyME Kinetic constant for H2 for hyME 10 106 MKAc-acME Kinetic constant for Ac for acME 50 103 MKCH4 Kinetic constant for CH4 for

AOM15 103 M

KH2-acet Kinetic constant for H2 foracetogenesis

10 107 M

KAc-acet Kinetic constant for Ac foracetotrophy

10 103 M

KDOC-ferm Kinetic constant for LMW-DOCfor fermentation

10 103 M

vmax-hySR Maximum rate of hySR 143 mol H2 L1 y1

vmax-acSR Maximum rate of acSR 074 mol Ac L1 y1

vmax-hyME Maximum rate of hyME 142 mol H2 L1 y1

vmax-acME Maximum rate of acME 071 mol Ac L1 y1

vmax-AOM Maximum rate of AOM 071 mol CH4 L1 y1

vmax-acet Maximum rate of acetogenesis 141 mol H2 L1 y1

vmax-actr Maximum rate of acetotrophy 071 mol Ac L1 y1

vmax-ferm Maximum rate of fermentation 083 mol C6H12O6 L1 y1

Average stoichiometric number 100 per electronGBQ-hySR Bioenergetic energy threshold

for hySR100 kJ mol1 (electrons)

GBQ-acSR Bioenergetic energy thresholdfor acSR

125 kJ mol1 (electrons)

GBQ-hyME Bioenergetic energy thresholdfor hyME


GBQ-acME Bioenergetic energy thresholdfor acME


GBQ-AOM Bioenergetic energy thresholdfor AOM


GBQ-acet Bioenergetic energy thresholdfor acetogenesis


GBQ-actr Bioenergetic energy thresholdfor acetotrophy


GBQ-ferm Bioenergetic energy thresholdfor fermentation


aQ10 38 for terminal metabolism (R3ndashR9 Table 1) and 20 for hydrolysis and fermentation(R1 R2)


Table 3 Physical model parameters and boundary conditions used to constrain the baselinesteady-state simulations (December 2004)

Parameter Description

Baseline valuea

UnitM1 M5

z Water depth 1500 2750 cmL Length of model domain 700 cmS Salinity 27 mdashTav Average bottom water

temperature28115 K

130 Porosity at x 0 078b 081b mdash13L Porosity at x L 067 072 mdash Depth attenuation coefficient

for porosity0009 003 cm1

v Sediment accumulation rate 002c 020c cm y1

ksw Thermal conductivity ofseawater

0006 W cm1 K1

kds Thermal conductivity of drysediment

0025 W cm1 K1

sw Density of seawater 1027 g cm3

ds Density of dry sediment 2500 g cm3

csw Specific heat capacity ofseawater

4184 J g1 K1

cs Specific heat capacity of drysediment

0300 J g1 K1

0 Bioirrigation coefficient atx 0

18d 20d y1

1 Attenuation coefficient 1 forbioirrigation

140 150 cm1


10 cm1

Db0 Bioturbation intensity in theupper layers

12e cm2 y1

DSO42

0 Diffusion coefficient for SO42 173f cm2 y1

DDIC0 Diffusion coefficient for DIC 160f cm2 y1

DDOC0 Diffusion coefficient for

LMW-DOC30g cm2 y1

DAc0 Diffusion coefficient for Ac 180f cm2 y1

DH2

0 Diffusion coefficient for H2 744f cm2 y1

DCH4

0 Diffusion coefficient forCH4(aq)

283f cm2 y1

DCH4(g)

0 Diffusion coefficient for CH4(g) 1400 10000 cm2 y1

kGF CH4(g) formation rate constant 1 102 y1

kdiss CH4(g) dissolution rate constant 1 107 M1 y1

xgas Approximate depth of CH4

bubbles300h 100h cm


Table 3 (Continued)

Boundaryconditions Description

Baseline valuea

UnitM1 M5

FPOCLABFlux of POCLAB to SWI 45 104 10 104 mol cm2 y1

FPOCMIDFlux of POCMID to SWI 00 23 105 mol cm2 y1

FPOCREFFlux of POCREF to SWI 25 105 27 104 mol cm2 y1

A0 Seasonal amplitude in TSWI

(Eq 13)65 K

Phase lag at the SWI (Eq 13 amp16)

058 y

Period of the seasonal signal(Eq 13 amp 16)

1 y

C0SO42 Measured SO4

2 concentration atx 0

22000 M

C0DIC Estimated DIC concentration at x 0

2000 M

C0DOC Estimated LMW-DOCconcentration at x 0

5 M

C0Ac Estimated Ac concentration at x 0

20 M

C0H2Estimated H2 concentration at x 0

01 nM

C0CH4Estimated CH4(aq) concentration

at x 010 M

C0CH4(g)Estimated CH4(g) concentration

at x 000

CLCH4(g)Concentration of CH4(g) at x L 30

CL All other species at x L Cx 0 mdash

aA single value applies to both coresbPorosity 13 at any depth x is calculated by 13 13L (130 13L) exp( x)cApproximated from 14C analysis (J Jensen pers comm)dBioirrigation at any depth x is calculated by

0 middot exp1 x

21 exp1 x

2

eIf 0 x 12 cm Db Db0 If x 12 cm Db 110 exp(0378( x Db0)) (Fossing et al2004)

fValue corresponds to infinite dilution in seawater at 5degC (Schulz 2000)gFrom Dale et al (2008)hDetermined by seismic survey (Laier and Jensen 2007)


no direct measurements were available to constrain the CH4(g) transport rate Thispermitted CH4(g) which accumulates at depth below the sulfate-reducing zone to diffuseupwards through the sediment and re-dissolve if the pore water was under-saturated withCH4(g) (see below) This approach is fully mass conservative and avoids the use ofnon-local sink terms to remove the accumulating gas (Martens et al 1998)

The dependence of DS on porosity and temperature (T K) followed Boudreau (1997)

DS DS

0

1 ln 1321 T 27315 (3)

where DS0 is the value for diffusion in seawater at 0 oC (Table 3) 1(1-ln(132 )) and (1)

corrects for tortuosity and T respectively values for each dissolved species werecalculated from Boudreau (1997) The T-dependency of DCH4(g) in addition to Db and required for the transient simulations was not considered in the model The validity of thisassumption is tested in section 3biii

ii Organic carbon decomposition and substrate turnover POC deposited at the sea floorwas degraded in the model to LMW-DOC by extracellular hydrolysis (R1 Table 1)(Bruchert and Arnosti 2003) The hydrolysis rate (mol C g-1y-1) of each POC fraction jwas described by

R1 j

fTkhyjPOCj (4)

where fT Q10TTref10 (5)

where khy-j refers to the first-order decay constants (y-1) for the jth fraction of POC (khyLABkhyMID and khyREF) and f (T) is the T-dependency of hydrolysis relative to the referencetemperature Tref (see below) Fermentation of LMW-DOC to DIC Ac and H2 (R2 Table 1Burdige 2006) provided the substrates for the terminal metabolic processes in the reactionnetwork (R3ndashR9)

Steady-state microbial biomasses were assumed based on the premise that microbialactivity rather than total cell numbers exerts the main control on substrate turnover intypical coastal marine sediments (Dale et al 2006) The reaction rate for each catabolicpathway (R3ndashR9) including fermentation (R2) for the specified stoichiometries wasdetermined by

dED

dt

i

fTvmaxiFKiFTi (6)

FKi ED

KEDi ED EA

KEAi EA (7)


FTi max 0 1 expGINSITUi GBQi

RT (8)

where vmax-i (mol ED L-1 y-1) is the maximum rate of electron donor (ED) utilization by thei-th catabolic pathway and FK and FT are the dimensionless kinetic and thermodynamicdrives for the reaction (Jin and Bethke 2005) In Eq 7 ED and EA represent the electrondonor and acceptor of the catabolic reaction respectively with corresponding half-saturation constants (KEDEA-I Dale et al (2008)) GINSITU (kJ mol-1 electrons) is the insitu (non-standard) Gibbs energy yield of the catabolic process and GBQ (kJ mol-1

electrons) is the Gibbs energy threshold for catabolism (assumed to be T-independentwithout supporting data) is the average stoichiometric number (Jin and Bethke 2005)and R is the gas constant (8314 J K-1 mol-1) FK and FT vary between 0 (total limitation ofED uptake) and 1 (no limitation) The product of FK and FT gives the total drive forreaction Parameter values are summarized in Table 2

The vmax-i values were calculated from the microbial growth yields following theapproach of Dale et al (2008) using a mean biomass concentration for Aarhus Bay ofapproximately 75108 cells cm-3 (B Cragg pers comm) The Arrhenius f (T) term in Eq6 provides the T-dependency of vmax-i relative to the reference temperature Tref of27815K A Q10 value of 38 has been determined experimentally for sulfate reduction inAarhus Bay by Fossing et al (2004) and we assumed that this Q10 value was applicable forthe microbial processes R3-R9 in Table 1 A Q10 value of 20 was prescribed for hydrolysisand fermentation (R1-R2) since their temperature response has been observed to beapproximately half that for SR (Weston and Joye 2005)GINSITU was calculated from the chemical composition of the pore water using

GINSITU G RT ln Q (9)

where Gdeg is the standard Gibbs energy of catabolism (kJ mol-1 electrons) at 28115 Kand corrected for biologically neutral pH conditions (Dale et al 2006) and Q representsthe activity quotient using activity coefficients from Dale et al (2008) Gdeg values werenot corrected for T in the transient simulations because the reaction rates change by only1 within the range 27615ndash28915 K For sulfate reduction (R3ndashR4) the measuredsulfide concentration (20 mM) in the SMTZ was used to calculate GINSITU

iii Dissolved and gaseous methane Exchange of methane between the dissolved andgaseous phases was assumed to be proportional to the departure between dissolvedmethane CH4(aq) and the local solubility concentration CH4 The rates of gas formationRGF and dissolution Rdiss were described by (R10-11 Table 1)

RGF kGFCH4aq CH4 for CH4aq CH4 (10)

Rdiss kdissCH4 CH4aqCH4g for CH4aq CH4and

CH4g 0(11)


where kGF (y-1) and kdiss (M-1 y-1) are the corresponding rate constants As a firstapproximation the magnitude of the kGF and kdiss were set sufficiently high to (i) preventover-saturation of the pore water and (ii) prevent the coexistence of CH4(g) and under-saturated pore water if CH4(aq) CH4 The assumption is based on the observations that nobubbles were observed in the cores above the gas horizon (ie close to gas equilibriumconditions) and that the solute profiles above this depth showed no obvious signs ofbubble-induced mixing of pore water

CH4 (mol L-1) depends on salinity (S) temperature (T) and pressure (P) A numericalmodel for calculating CH4 over a wide range of S T and P has been presented by Duan etal (1992) Based on his work we constructed a simplified analytical approximation whichis computationally efficient Three successive linear regressions were performed todetermine the dependence of CH4 on S T and P respectively which were then folded intoa ruled hyper-surface and expressed by the following 3rd degree polynomial

CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)

CH4 concentrations calculated with this formula predict CH4 for ranges of S (1-35) T(27315-29015 K) and P (1-30 atm) relevant to temperate aquatic environments and areidentical to those derived from the fully-implicit iterative formulation of Duan et al (1992)to within 3 The formula assumes that the total pressure of the gas in the sediment P isexclusively due to methane and water vapor (Duan et al 1992) In this study thecontribution of other gases (eg CO2 N2) was neglected since their dissolved concentra-tions in Aarhus Bay sediments 500 M N2 (assumed Martens and Berner 1977) and700 M CO2 (calculated) were well below their respective in situ solubility concentra-tion

iv Heat transport and boundary conditions In the baseline steady-state simulations usedfor the model calibration boundary conditions for solutes and CH4(g) at the sediment-waterinterface (SWI) were imposed as fixed concentrations corresponding to either measured orexisting literature values (Table 3) T at the upper boundary was set to the value measuredduring sampling in December 2004 (281 K) and the flux of POC to the sediment surfacewas adjusted to fit the experimental data as described in the following section Solutes andsolids at the lower boundary were prescribed with zero concentration gradients (Table 3)For CH4(g) a fixed concentration equivalent to a volumetric gas content of 3 (gasvolumetotal sediment volume see Martens et al (1998) for calculation) was imposed atthe base of the model This value is based on previous estimates and measurements of gascontent in Eckernforde Bay (Abegg and Anderson 1997 Martens et al 1998 Anderson etal 1998 Mogollon et al 2008) ndash an environment geochemically similar to Aarhus Bay

Different boundary conditions were required for the transient simulations where T andPOC were modified to represent the seasonal fluctuations at the SWI The variation in T at


the SWI (TSWI) was implemented using a sinusoidal function between maximum andminimum values around the annual mean Tav

TSWI Tav A0 sin 2t

(13)

where (y) is the period of the signal and A0 (K) is the seasonal amplitude at the SWI Thephase lag (y) synchronized the boundary condition with the measured T data (Table 3)The spatial and temporal variation of T was calculated by solving the heat transportequation subject to thermal diffusion

T

t DT

2T

x2 (14)

where DT (cm2 y-1) is the thermal diffusivity of the saturated sediment calculated by

DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)

where k is the thermal conductivity (W cm-1 K) is density (g cm-3) c is the specific heatcapacity (J g-1 K-1) and subscripts sw and ds denote seawater and dry sedimentrespectively (Woodside and Messmer 1961) (Table 3) Due to the high thermal diffusivityheat transport due to sediment burial bioturbation and bioirrigation are negligible andignored (see Section 3bi) The bottom of the model core (700 cm) experiences a negligibleeffect from the temperature variations in seawater and a zero thermal gradient conditionwas prescribed for T at the lower boundary

The seasonal variability in POC deposition at the SWI (FSWI mol C cm-2 y-1) was alsoconsidered despite only being important in the uppermost sediment layers (Fossing et al2004) No data were available to accurately constrain FSWI and therefore a sinusoidalfunction was used which sums the fluxes of each POC fraction j

FSWI j

FPOCj1 sin 2t

(16)

where the average value of each flux (FPOC-j ) was set to the value used in the baselinesimulation (Table 1) so that the seasonal flux varied from 0 to 2FPOC in phase with TSWIThis amplified the effect of seasonal variations and the simulations should thereforeprovide an upper limit for the intra-annual variability in sulfate and methane cycling

3 Results and discussion

a Baseline simulations

The model results for the baseline simulation of the sediment biogeochemistry atstations M1 and M5 calibrated using the data measured in fall 2004 are shown in Figure 1The simulated SO4

2- and CH4(aq) concentrations at M1 and M5 compare well with the


measured data (Fig 1af) and the corresponding model results for the measured sulfatereduction (SR) rate (assumed to be the sum of hySR (R3) and acSR (R4) Table 1) alsocompare favorably (Fig 1bg) khyLAB and khyMID (Eq 4) were constrained from themeasured SR rate above the SMTZ since POC is almost entirely oxidized by SR below thetop 5 cm (Fossing et al 2004) The higher SR rate at M1 alludes to a higher abundance oflabile organic substrate than at M5 At both sites the SR rate presents two maxima one atthe surface and another deeper down at the SMTZ Here SR is coupled to the anaerobicoxidation of methane diffusing upwards from depth which consumes methane at maxi-mum rates of 14 and 93 nmol cm-3 d-1 for M1 and M5 respectively similar to 14CH4

radiotracer AOM rates (Knab et al unpublished data) The peak of the SMTZ defined atthe depth of equimolar SO4

2- and CH4(aq) concentrations is located at 221 cm at M1 and 63cm at M5 (solid horizontal lines) However it is important to keep in mind that the SMTZis not restricted to a single specific depth but extends along a certain domain where CH4

and SO42- coexist Repeated coring over the 2 year sampling period further suggests that at

both sites the SMTZ depth shifts vertically by up to 80 cm at M1 and 16 cm at M5 (dashed

0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000

LMW-DOC prod(nmol C cm-3 d-1)

(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60

AOM SR(nmol cm-3 d-1)

(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot

Figure 1 Steady-state simulated (lines) geochemical and measured (points) profiles for December 2004at stations M1 (top row) and M5 (bottom row) (af) SO4

2- CH4(aq) modeled CH4(g) (shaded) and CH4(bg) Rate of sulfate reduction (SR) and AOM (ch) Rate of production of LMW-DOC (di) DICconcentration and (ej) total POC concentration The solid horizontal lines in (abfg) indicate thedepth of the SMTZ (zSMTZ) and the dashed horizontal lines show the extent of variability of observed insamples from repeated coring at the same station Note the breaks in the axes


horizontal lines) This variability is not an artifact introduced by alignment of the twocoring devices since the variability is greater than the uncertainty (3 cm for M1 and M5)attributed to the sediment lost from the gravity core

The different SMTZ depths in the baseline simulations between M1 (221 cm) and M5(63 cm) cannot be attributed to an enhanced flux of SO4

2- into the sediment by the mixingand burrowing action of indwelling fauna because the model data are simulated withidentical rates of bioturbation and near-equivalent rates of bioirrigation (Table 3) It ismore likely that the rate of LMW-DOC production by POC hydrolysis is the determiningvariable (Westrich and Berner 1984 Bruchert and Arnosti 2003) For example decreasedfermentation of LMW-DOC to Ac and H2 will lead to lower rates of SR and methanogen-esis enhanced SO4

2- penetration into the sediment and a deeper SMTZ At M1 best fits tothe SR rates are attained with a LMW-DOC production rate at the surface (130 nmol Ccm-3 d-1 Fig 1c) which is 4 times greater than at M5 (31 nmol C cm-3 d-1 Fig 1h) possiblybecause the water column is only 15 m deep compared to 27 m at M5 and thus M1receives a higher amount of labile POC (Table 3) Flushing of the pore water bybioirrigation prevents SO4

2- from becoming depleted in the surface layers Moreover thislabile carbon substrate is quickly exhausted below the bioturbated zone at M1 andLMW-DOC production decreases sharply at 25 cm depth The apparent absence of SRbetween 25 cm and the top of the SMTZ (160 cm) thus indicates a lack of degradable POCaccording to the model (Fig 1b) At M5 the measured rate profiles are best reproducedusing the additional mineralization of POCMID which contributes to hydrolysis below theupper layers (Fig 1h) This leads to more uptake of SO4

2- below the irrigated zone andreduced penetration of SO4

2- into the sediment Integrated over the whole sediment SRequals 603 nmol cm-2 d-1 at M1 and 397 nmol cm-2 d-1 at M5 (Table 1) which arecomparable to the measured rate of 470 nmol cm-2 d-1 in the upper mixed layer of AarhusBay reported by Thamdrup et al (1994) At both M1 and M5 90 of the SO4

2- issupplied by bioirrigation with the remaining fraction supplied by diffusion bioturbationand input through burial It must be noted however that the fraction of SO4

2- added bybioirrigation implicitly accounts for the recycling of SO4

2- by re-oxidation of hydrogensulfide using O2 (Glud et al 2003 Fossing et al 2004) a process not included in themodel

The importance of the labile substrate in the upper layers at M1 is further supported bythe low ratio of the depth integrated rates of AOM to total SR which is a measure of thesignificance of methane as substrate source for SR AOM fuels only 4 of SR at M1compared to 28 at M5 despite the very obvious draw down of SO4

2- to the SMTZ at M1These findings broadly agree with observations by Dale et al (2008) for Skagerraksediments whereby the POC depositional conditions and relative rates of terminalmetabolism can exhibit large differences within the same local geographical area

The total rate of carbon degradation in the sediment was constrained by the measuredDIC concentration (Fig 1di) The DIC shows a more gradual increase with depth at M1than M5 even though surface SR rates were far higher This arises from more rapid


removal through irrigation of the DIC produced from POCLAB At M5 the mineralizationof POCMID below the irrigated zone allows DIC to accumulate At both stations the DICconcentration stabilizes below the SMTZ suggesting that there is very little mineralizationof POCREF in the sediment This result is also supported by the uniform POC concentrationprofiles (Fig 1ej) On this basis the reactivity of POCREF (khyREF) was set to zero whichmeans that methanogenesis does not take place in the deeper sediment layers because thereis no burial of reactive POC below the SMTZ In reality methanogenesis actually occurs inthe sediment (B Cragg pers comm) but the rates are not easily resolvable from the DICdata Therefore in order to fit the measured methane data and the depths of free methanegas observed on the seismic profiles (300 cm at M1 and 100 cm at M5 Laier andJensen 2007) (Fig 1af) a source of methane gas had to be specified at the lower modelboundary DCH4(g) was then constrained by fitting the depth of the SMTZ and set equal to1400 cm2 y-1 at M1 and 10000 cm2 y-1 M5 (Table 3) An alternative model approachwould obviously be to attribute all the CH4(g) to the in situ production from POCREF

mineralization However this resulted in DIC concentrations up to 6 times higher thanmeasured (data not shown) a finding which confirms that in situ methanogenesis ratesmust be low throughout the core

Together the model provides compelling evidence that the CH4(g) in these cores either(i) ascends in the sediment along lateral unconformities or cracks in the sediment matrix(Boudreau et al 2005) or (ii) originates from a deeper organic-rich sediment depositedduring the initial stages of the Holocene transgression (Jensen and Laier 2003 Laier andJensen 2007) Transport of CH4(g) from the underlying deep late glacial sediments isunlikely since they contain very little organic matter (Jensen and Laier 2003) Thesampling campaign was not designed to investigate the mechanisms of gas transport andthis issue remains unresolved Further chemical analysis of deep sedimentary layersincluding pore water 13C data may be needed to support either hypothesis

b Transient simulations

Seasonal forcings of T and POC flux to the SWI at M1 and M5 are described by Eq 13and (16) All other internal model parameters and boundary conditions remain unchangedfrom the baseline simulations described above Imparting from the baseline simulations asinitial conditions the simulations are tracked with the time-varying boundary conditionsuntil yearly-averaged steady state is reached At this point there is no inter-annualvariability in T species concentrations or rates for any given day of the year

i T and POC forcings Temperature affects the magnitude of transport and reaction byimpacting on vmax through f(T) FT directly through T and indirectly through GINSITU thesolute diffusion coefficients DS and the methane solubility CH4 Due to lack of databioturbation and bioirrigation were assumed independent of T The implications of thisassumption are briefly addressed below


Figure 2a compares the measured bottom water temperature (TSWI) in Aarhus Bayduring the entire year of 2004 with the temperature imposed at the sediment surface in themodel TSWI shows a variation of 13 K between 276 K (3oC) in winter (February) and 289K (16oC) in summer (August) which is typical for this environment (Thamdrup et al1994 Glud et al 2003) Although the measured data show a departure between the startand end of the year the intra-annual variability is significantly larger and can beapproximated with a sinusoidal function

The transient T profiles in the sediment were calculated by integrating Eq 14 using TSWI

as an upper boundary condition No experimental data are available to verify the modeled Tdistribution yet studies have shown that heat propagation in sediments can be faithfullyreproduced from porosity data and the fundamental thermal properties of sea water andsedimentary material (Woodside and Messmer 1961) For instance the calculated thermaldiffusivity (DT) corresponding to 28165 K and a porosity of 074 is 62105 cm2 y-1which is similar to values reported by Matisoff (1980) and Jackson and Richardson (2001)for marine sediments The theoretical seasonal evolution of T predicted by Eq 14 is shownin Figure 2b and displays an e-folding depth of 120 cm (the depth at which the seasonalamplitude of T decreases to 1e of its value at the sediment surface) which is againcomparable to calculations based on measured vertical T profiles (Matisoff 1980 Westrichand Berner 1984 Jackson and Richardson 2001) The time-lag in diffusion of heatthrough the sediment occasionally produces inverted profiles where T is greater at depththan at the surface (eg January) in addition to non-monotonous profiles where transientmaxima and minima with depth are generated (eg May and November)

The reduced seasonal amplitude of T variations at the depth of the SMTZ (zSMTZ) is alsovery obvious (Fig 2b) with a change of 10 K at M5 and only 3 K at M1 where theSMTZ is deeper This variation is plotted for M1 and M5 against TSWI in Figure 2cdrevealing a cyclic variation of heat at these sites The time lag and dampening of T withdepth results in a Lissajous curve which means that when 27615 K TSWI 28915 Ktwo different possible values of T can be obtained in the SMTZ for a given TSWI dependingon whether TSWI is increasing (winter-to-summer) or decreasing (summer-to-winter) Theeccentricity of the resulting ellipsoid is more pronounced for M5 since the SMTZ is locatedcloser to the SWI and experiences less time-lag and thermal dampening through thesediment In contrast TSMTZ at M1 experiences a greater degree of decoupling from TSWI

and shows a broader more horizontal loop Here the maximum TSMTZ occurs inNovember 3 months after the surface maxima in August This suggests that time-lags inmicrobial substrate turnover rates driven by changes in T can be expected to increase withincreasing depth into the sediment It follows also that the dynamics of CH4 dissolution andCH4(g) formation which are directly dependent on solubility (Eq 10ndash12) will presentsimilar lags

The seasonal change in modeled POC concentration is only apparent in the uppermostfew cm of the sediment despite the relatively large seasonal amplitude in depositional flux(Eq 16) (data not shown) Below the upper mixed depth (25 cm) the POC concentration is


Month in 2004

275

280

285

290

TS

WI (

K)

(a)

jan feb mar apr may jun jul aug sep oct nov dec

275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)

Figure 2 (a) Bottom water temperature (TSWI) measured during 2004 (points) and TSWI imposed onthe transient simulations (b) Depth distribution of T in the sediment at M1 the T distribution forM5 is almost identical Each line corresponds to a calendar month indicated by the numerals on theupper axis The horizontal dashed lines indicate the depth of the SMTZ (zSMTZ) at M1 and M5(cd) Annual evolution of T at zSMTZ (TSMTZ) against TSWI for M1 and M5


constant throughout the year and shows no seasonal signal An order of magnitude for theage of the particulate material in the bioturbated layer can be approximated by the ratio ofthe bioturbation depth (20 cm) and the burial rate (02 cm y-1) as 100 y (at M5) Since theperiodicity of the POC input is only 1 y the burial rate is too slow even at M5 to allow theseasonal variability in POC flux to be preserved in the sediment profiles (cf Burdige2006)

ii Seasonal dynamics of redox processes The maximum seasonal change in modeledmethane (CH4(aq)) and sulfate (SO4

2-) concentrations and rates (SR and AOM) areshown in Figure 3 The intra-annual variability reveals contrasting patterns at M1 and M5owing to the different rates and depth distribution of LMW-DOC production and Tdiscussed previously This is expressed in a large SO4

2- in the surface layers at M1 of 700nmol cm-3 (Fig 3a) and a maximum SR of 60 nmol cm-3 d-1 (Fig 3b) At M5 whichreceives less POCLAB SO4

2- and SR are significantly lower (Fig 3cd) The integratedrates of SR range from 566-631 nmol SO4

2- cm-2 d-1 at M1 and 205-392 nmol SO42- cm-2 d-1

at M5 (Table 1) For comparison this is much lower than measured for Cape LookoutBight (3300-7800 nmol cm-2 d-1) where organic carbon mineralization rates are roughly 10times higher (Crill and Martens 1987) The seasonal differences in the STMZ are evenmore pronounced with much larger changes in SO4

2- CH4(aq) SR and AOM at M5compared to M1 (Fig 3) due to the higher seasonal variation of T at M5 (10 K and 3 K atM1) (Fig 2b) Thus whereas the seasonal change in substrate turnover at the surface ismostly driven by the organic carbon input (Westrich and Berner 1988) temperature is themajor factor driving the variation in rates in the SMTZ The seasonal range in the depthintegrated AOM rate (yenAOM Table 1) is small at M1 (20-24 nmol cm-2 d-1) and muchlarger at M5 (76-178 nmol cm-2 d-1) the latter being comparable to Eckernforde Bay(51ndash150 nmol cm-2 d-1 Treude et al 2005) Overall the maximum variability in SR andAOM rates in the SMTZ is roughly equal in magnitude to the baseline values at M1 (Fig1b) and M5 (Fig 1f)

The depth of the gas horizon below the SMTZ may also be important for the seasonalvariability in methane cycling because T-induced changes in gas solubility will impact onCH4(aq) concentration At M5 CH4(aq) concentration exhibits seasonal changes of 820nmol cm-3 compared to only 150 nmol cm-3 at M1 (Fig 3ac) Moreover free gas is locatedmore closely to the SMTZ at M5 whereas at M1 changes in CH4(aq) concentration due togas formation and dissolution occur more than 50 cm below the SMTZ Consequentlywhereas the modeled annual evolution of yenAOM at M1 can be mostly attributed the kinetictemperature effect only the oscillation at M5 is also influenced by seasonal changes in gassolubility and methane flux to the SMTZ

A common procedure for balancing mass fluxes in aquatic sediments relies on usingmeasured solute concentration profiles to derive diffusive transport rates However giventhe seasonal change in rates (Fig 3) this approach must be treated with caution Toillustrate this point in more detail Figure 4 shows the dependency of the maximum local


AOM rate on the temperature at zSMTZ (TSMTZ) The rate of AOM is the product of vmaxwhich depends on T through the Arrhenius term f(T) (Eq 6) and the dimensionless kinetic(FK) and thermodynamic (FT) factors which are shown individually in the insets (Fig4ab) The AOM rate increases from a minimum in spring to a maximum in fall at M1 andsummer at M5 However the seasonal evolution of the AOM rate at zSMTZ is not a simpleresponse to the local temperature and a hysteretic effect occurs with a greater verticalbroadness of the loop in summerfall than winterspring Thus similar to the relationshipbetween TSWI and TSMTZ (Fig 2bc) two possible rates are possible for each temperature

0 5 10 700 800 900

∆SO42- ∆CH4(aq)(nmol cm-3)

400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60

∆SR ∆AOM(nmol cm-3 d-1)

400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM

Figure 3 (a) Maximum annual change in SO42- (SO4

2- line) and CH4(aq) (CH4(aq) shaded)concentrations at M1 (b) Maximum annual change in sulfate reduction (SR line) and AOM rate(AOM shaded) at M1 (c) as (a) for M5 and (d) as (b) for M5


05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

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mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug

Figure 4 (a) Annual evolution of the local AOM rate versus temperature (TSMTZ) at the depth of theSMTZ for M1 The inset plots show the (dimensionless) variation in f(T) kinetic drive (FK) andthermodynamic drive (FT) for AOM as a function of TSMTZ (b) as (a) for M5


depending on the season However this is not the same Lissajous behavior as observed inFigure 2cd because here the AOM is plotted against the local temperature TSMTZ Theoverall range of rate values observed over one year is determined by the f(T) term sincerelative to the other factors this term has the largest range of variation The hysteresis onthe other hand arises from the combined effect of the FT and FK terms Since FT and FK

depend on chemical concentrations as well as temperature it can be hypothesized that thetime lags in the rates of production consumption and diffusive transport of solutes areresponsible for the hysteresis It is unlikely that this hypothesis could be substantiated fromdirect observation because of the small-scale heterogeneity of natural sediments andanalytical uncertainty

Figure 5 shows the seasonal evolution of depth integrated AOM rates as a function of thebottom water temperature (TSWI) a parameter routinely measured in the field Because TSWI

is non-linearly related to TSMTZ the yenAOM rate evolves with TSWI in a non-intuitivemanner Again the model predicts significant differences in yenAOM rate for identical TSWI

from spring to fall For example at 287 K the yenAOM rate at M5 equals either 130 nmolcm2 d-1 in fall or 150 nmol cm2 d-1 in summer Moreover by comparison to the baselineyenAOM rate (dashed horizontal line) the model shows that there is a very strong prospectfor erroneous methane budget calculations if yenAOM rates pertaining to a single time eventare scaled up to yearly time scales This is especially true for M5 which experiences alarger seasonal range in T Additionally only two values are predicted for each TSWI herebecause of the regular sinusoidal forcing imposed in the model Yet considering thenatural fluctuations in TSWI in the field and the high thermal diffusivity multiple AOM ratevalues for the same TSWI may be expected

275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate

Figure 5 (a) Annual evolution of the depth-integrated AOM rate (yenAOM) versus T at thesediment-water interface (TSWI) at M1 The dashed horizontal line corresponds to the baselinesimulation rate (Table 1) (b) as (a) for M5


iii Seasonal displacement of the SMTZ depth (zSMTZ) Figure 6 shows that SO42- penetra-

tion varies during the course of one year with a maximum displacement of 2-3 cm at M5and 1 cm at M1 The changes in zSMTZ are thus much smaller than those of theexperimental observations (dashed lines in Fig 1af) Larger seasonal changes in measuredsulfate penetration have also been reported at Cape Lookout Bight (20 cm Klump andMartens 1989 Alperin et al 1994) Eckernforde Bay (10 cm Treude et al 2005) andLong Island Sound (15 cm Westrich and Berner 1984) The shift in modeled zSMTZ

remains limited because even though the maximum seasonal changes in concentrationsand rates are relatively large (Fig 3) the turnover time of SO4

2- and CH4(aq) at any givenmoment in the SMTZ is long (tt 05-2 years) This allows sufficient time for SO4

2- andCH4(aq) to diffuse over a significantly longer distance ((4 ttDS)1frasl2 15 cm) and replenishthe relatively small fraction of SO4

2- and CH4(aq) removed from the porewater by microbialactivity In the following discussion we explore the mismatch between the modeled andobserved zSMTZ

It could be argued that the model underestimates the microbial temperature effect Themicrobial response to temperature (f(T) Eq 6) employs a fixed Q10 value of 38 forterminal metabolism and 20 for hydrolysis and fermentation which implicitly assumesthat the activation energy (Ea) of the rate remains constant However Westrich and Berner(1988) reported an inverse relationship between Ea and the SR rate with sediment depthThis was interpreted as the effect of increasing recalcitrance of organic matter leading to anapparent increase in the Ea (ie Q10) for SR Crill and Martens (1987) reported similarfindings for seasonally depth-integrated SR rates in Cape Lookout Bight sediments Weobserved that the seasonal variability in zSMTZ was insensitive to temporal and spatialvariations in the Q10 parameter (data not shown) This can be explained by the strong

0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct

Figure 6 (a) Maximum and minimum modeled concentration profiles of SO42- and CH4(aq) in the

SMTZ at M1 The grey points highlight the depth of equimolar SO42- and CH4(aq) concentrations

(b) as (a) for M5 Note the difference depth and concentration scales


controls by kinetic and bioenergetic factors which limit the rate of AOM to 01 of vmax

(ie FK FT 0001) The degree of this limitation appears to be characteristic ofsubstrate-starved microbial networks (Dale et al 2008) and is too strong for Q10

variations to have any real impact on zSMTZ The role of Ea is probably much moreimportant in Cape Lookout Bight where organic substrates are in abundance and sulfatereducing bacteria at the base of the SR zone become limited by SO4

2- during much of theyear (Alperin et al 1994) In Aarhus Bay it appears therefore unlikely that the shifts inzSMTZ could arise from a direct T effect on microbial activity within the SMTZ or for thesame reason from short-term time lags in microbial growth (Hoehler et al 1999)

It is worth considering further the reasons why Cape Lookout Bight and EckernfordeBay display relatively large seasonal variations in the depth of SO4

2- penetration Thesediment geochemistry at these sites is generally comparable to Aarhus Bay with freemethane gas formation below the SR zone and large fluctuations in TSWI Howeversediment accumulation rates in these systems are relatively high (10 cm y-1 and 1 cm y-1respectively) and bioturbation is limited to the upper 1-2 cm or even absent (Martens et al1998 Nittrouer et al 1998) This means that SO4

2- input in the deeper sediment layersoccurs only by burial and diffusion across the sediment water interface plus to a lesserextent oxidation of dissolved sulfide in the surface sediment (Chanton et al 1987)Consequently high summer SR rates coupled to LMW-DOC production will more rapidlydeplete the SO4

2- pool during summer than during other periods of the year (Crill andMartens 1987 Alperin et al 1994 Treude et al 2005) For instance Alperin et al (1994)showed that SO4

2- diffuses to greater depths only at the end of the fall when production ofLMW-DOC slows down In contrast bioturbation and especially bioirrigation in AarhusBay continually replenish the SO4

2- pool and buffer the effect of seasonal SR variation thuspartially attenuating the role of T on pore water chemistry (Fossing et al 2004)

Irrigation intensity may vary significantly at the same sampling location (Heilskov et al2006) and the magnitude and timing of this process do not necessarily follow a straightfor-ward seasonal pattern (Aller and Aller 1992 Schluter et al 2000 Forster et al 2003)Studies of North Sea sediments by Forster et al (2003) showed that the seasonal variabilityin the irrigation rate constant (0) was statistically comparable to the variability amongadjacent cores sampled simultaneously and they attributed this anomaly to spatialheterogeneity of faunal abundance These authors were further able to show that thepumping action of burrowing infauna increased under hypoxic conditions (O2 50 M) asthe animals became oxygen stressed Although no O2 data were measured during oursampling in Aarhus Bay bottom water O2 concentrations of 50 M appear typical for theend of summer (Thamdrup et al 1994 Glud et al 2003) Without the necessary data weare unable to determine precisely the quantitative significance of seasonal changes inbioirrigation with the model Intuitively though and considering the time scales of SO4

2-

diffusion one can expect seasonal fluctuations in bioirrigation to have little impact on thedownward flux of SO4

2- and zSMTZ The time required for SO42- to diffuse from below the

irrigated depth (15 cm) to the SMTZ is about 250 y at M1 and 18 y at M5 Intra-annual


variations in SO42- concentration due to bioturbation and bioirrigation will thus be

dampened by diffusion and tend not to be preserved in the deeper portion of the soluteprofiles Periodicities in sea floor bioirrigation on multi-decadal time scales will berequired to engender cyclicity in zSMTZ (Lasaga and Holland 1976 Burdige 2006)

Pore water exchange through bioirrigation is a much more complex process thansuggested by the 1-D non-local function assumed in the model (Table 3) Even though thisapproach provides a valuable means of extracting quantitative information on squeezedpore water samples (Berg et al 1998) the natural variation in burrow geometry size anddensity leads to particularly complex solute exchange process (Aller and Aller 1992Meile et al 2005 Meysman et al 2006) Furthermore the density of macro-fauna inAarhus Bay is highly variable (2800 700 m2 Glud et al 2003) which makes localheterogeneity in bioirrigation rates very likely We tested the sensitivity of zSMTZ to thebioirrigation intensity by applying the same relative standard deviation to the maximumbioirrigation rate constant (0) and irrigation depth (1) at each site and re-running thebaseline simulation With enhanced SO4

2- exchange zSMTZ showed a total displacement of36 cm at M1 and 10 cm at M5 (Table 4) which is more comparable to the variabilityobserved in the field data (80 cm at M1 and 16 cm at M5) The natural spatial heterogeneityin irrigation could in theory account for the apparent seasonal variability in zSMTZ but thisrequires that the same spatial differences in bioirrigation (faunal abundance) should bemaintained within the 50x50 m sampling area on the time-scale of SO4

2- diffusion to theSMTZ (up to 250 y at M1) Because this seems improbable we can confidently eliminatea significant effect of bioirrigation intensity on either intra- and inter-annual variations onsulfate penetration at M1 or M5

Therefore the model suggests that the effects of seasonal or long-term variability inforcing at the sediment surface are not sufficient to account for the observed seasonal shiftsin zSMTZ at each sampling station Consequently to reconcile model and analytical data thechanges in zSMTZ must be driven by processes originating from below the SMTZ ie theupward transport of methane gas The amount of CH4(g) transported upwards depends onthe specified lower boundary gas volume (3 Table 3) and the apparent diffusioncoefficient (DCH4(g)) which is an order of magnitude higher than the molecular diffusioncoefficient for CH4(aq) Even so we observed that a strong seasonal T-dependency ofDCH4(g) as well as the rates of gas formation and dissolution (kGF kdiss) always had minoreffect on zSMTZ (data not shown) On the other hand the change in zSMTZ due to a 25

Table 4 Depth of the SMTZ ( zSMTZ) following a 25 change in bioirrigation intensity (Bio) thegas diffusion coefficient (DCH4( g)) and gas concentration at the lower boundary (CL-CH4( g)

)relative to the apparent seasonal changes in the measured chemical data The simulations wereperformed at steady state

Data 25 Bio 25 DCH4(g) 25 CL-CH4(g)

M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9


change in DCH4(g) and the boundary gas volume showed very different results under steadystate conditions (Table 4) The 25 variability is not intended to embrace the confidenceinterval of the parameterization but rather illustrate the sensitivity of zSMTZ to DCH4(g) andthe boundary gas volume The results show that zSMTZ is sensitive to DCH4(g) at M5 but notat M1 because of the lower DCH4(g) used to model the data at this site (1400 cm2 y-1) Theimposed gas volume has much more impact on zSMTZ at M1 which undergoes a maximumdisplacement of 34 cm and also for M5 which shows a variation of 9 cm We thusconclude that different vertical gas transport fluxes within the same 50x50 m sampling areaaccount for most of the apparent seasonal displacement of the SMTZ However withoutmeasured gas volume data we are presently unable to identify the relative importance ofDCH4(g) versus gas occupancy The way which gas is transported in natural sediments is notfully understood but the high capillary forces within consolidated sediments are likely tolimit migration of zSMTZ through fracturing (Sills and Wheeler 1992 Boudreau et al2005) Our results support the findings of Laier and Jensen (2007) who postulated thatenhanced gas transport occurs throughout the Baltic Sea region and which could reflect thecontrasting lithology of the Holocene marine units

4 Conclusions

A transient reactive-transport model (RTM) of sulfate and methane cycling in shallowmarine sediments of Aarhus Bay has been developed to study the seasonal dynamicsimposed by variations in temperature and organic carbon deposition fluxes The verticalpropagation of temperature through the sediment core was explicitly accounted for in theRTM by the heat equation The model implementation was verified by comparing thesimulated vertical solute profiles and sulfate-reduction rates against field data collected inDecember 2004

Model results reveal that the transient behavior imposed by the fluctuating temperaturedeeply influenced the dynamics of the sulfate-methane transition zone (SMTZ) Asignificant hysteresis-type behavior between local temperature and rates of anaerobicoxidation of methane (AOM) was obtained Time lags due to the propagation of heat fromthe sediment surface down to the SMTZ add further complexity if AOM rates areinvestigated against temperature at the sediment-water interface ndash a measurable quantityTherefore the large seasonal evolution in biogeochemical process rates cannot beconstrained from the knowledge of the seasonal evolution of temperature in the overlyingwater alone

The large variations in reaction rates were barely recorded in the time evolution of thesolute concentrations due to smearing by molecular diffusion Comparison betweenmodeled and measured profiles revealed a complete failure of the model to simulate theapparently large seasonal shifts in the depth of the SMTZ observed in cores sampledrepeatedly from the same 5050 m sampling stations over 2 years The most likelyexplanation is that the SMTZ does not exhibit seasonal fluctuations at all but is insteadsensitive to the spatial heterogeneity of gas transport and to a lesser extent pore water


irrigation rates Consequently methane budgets of Aarhus Bay sediments must not onlyaccount for the seasonal change in AOM rates due to temperature but also for the naturalvariability in the gas depth and faunal activity in the surface sediments This means thatmultiple sediment core extractions will be required to calculate system-scale chemicalbudgets of Aarhus Bay sediments within an acceptable standard deviation

Acknowledgments We would like to thank Captain P Nathansen of StF 57 Henry for skillfulgravity coring Joslashrn Bo Jensen for information on the seismic data Tanja Quottrup for assistanceduring sampling and analyses and Vincent Mastalerz for assisting with the methane solubilitycalculations We are also grateful to DHI Water amp Environment (Denmark) for providing the bottomwater temperature data AWD and DRA were financially supported by Netherlands Organization forScientific Research (NWO VIDI grant no 86405007 and no 81302008 and respectively) and theEuropean Commission (METROL project EVK3- CT-2002-00080)

REFERENCESAbegg F and A L Anderson 1997 The acoustic turbid layer in muddy sediments of Eckernfoerde

Bay Western Baltic methane concentration saturation and bubble characteristics Mar Geol137 137-147

Aller R C and J Y Aller 1992 Meiofauna and solute transport in marine muds LimnolOceanogr 37 1018-1033

Alperin M J D B Albert and C S Martens 1994 Seasonal variations in production andconsumption rates of dissolved organic carbon in an organic-rich sediment Geochim Cosmo-chim Acta 58 4909-4930

Anderson A L F Abegg J A Hawkins M E Duncan and A P Lyons 1998 Bubble populationsand acoustic interaction with the gassy floor of Eckernforde Bay Cont Shelf Res 18 1807-1838

Berg P N Risgaard-Petersen and S Rysgaard 1998 Interpretation of measured concentrationprofiles in sediment pore water Limnol Oceanogr 43 1500-1510

Berner R A 1980 Early Diagenesis A Theoretical Approach Princeton University Press 241 ppBoetius A K Ravenschlag C J Schubert D Rickert F Widdel A Gieseke R Amann B B

Joslashrgensen U Witte and O Pfannkuche 2000 A marine microbial consortium apparentlymediating anaerobic oxidation of methane Nature 407 623-626

Boudreau B P 1997 Diagenetic Models and Their Implementation Modelling Transport andReactions in Aquatic Sediments Springer-Verlag 414 pp

Boudreau B P C Algar B D Johnson I Croudace A Reed Y Furukawa K M Dorgan P AJumars A S Grader and B S Gardiner 2005 Bubble growth and rise in soft sediments Geology33 517-520

Bruchert V and C Arnosti 2003 Anaerobic carbon transformation experimental studies withflow-through cells Mar Chem 80 171-183

Burdige D J 2006 Geochemistry of Marine Sediments Princeton University Press 609 ppChanton J P C S Martens and M B Goldhaber 1987 Biogeochemical cycling in an organic-rich

coastal marine basin 7 Sulfur mass balance oxygen uptake and sulfide retention GeochimCosmochim Acta 51 1187-1199

Crill P M and C S Martens 1987 Biogeochemical cycling in an organic-rich coastal marine basin6 Temporal and spatial variations in sulfate reduction rates Geochim Cosmochim Acta 511175-1186

Dale A W P Regnier N Knab B B Joslashrgensen and P Van Cappellen 2008 Anaerobic oxidationof methane (AOM) in marine sediments from the Skagerrak (Denmark) II Reaction-transportmodeling Geochim Cosmochim Acta doi 101016jgca200711039


Dale A W P Regnier and P Van Cappellen 2006 Bioenergetic controls on anaerobic oxidation ofmethane (AOM) in coastal marine sediments A theoretical analysis Am J Sci 306 246-294

Duan Z N Moller J Greenberg and J H Weare 1992 The prediction of methane solubility innatural waters to high ionic strength from 0 degrees to 250 degrees and from 200 to 1600 barGeochim Cosmochim Acta 56 1451-1460

Forster S A Khalili and J Kitlar 2003 Variation of nonlocal irrigation in a subtidal benthiccommunity J Mar Res 61 335-357

Fossing H P Berg B Thamdrup S Rysgaard H M Soslashrensen and K Nielsen 2004 A modelset-up for an oxygen and nutrient flux model for Aarhus Bay (Denmark) National EnvironmentalResearch Institute (NERI) Technical Report 483 68 pp

Fossing H T G Ferdelman and P Berg 2000 Sulfate reduction and methane oxidation incontinental margin sediments influenced by irrigation (South-East Atlantic off Namibia) GeochimCosmochim Acta 64 897-910

Fossing H and B B Joslashrgensen 1989 Measurement of bacterial sulfate reduction in sedimentsEvaluation of a single-step chromium reduction method Biogeochemistry 8 205-222

Glud R N J K Gundersen H Roslashy and B B Joslashrgensen 2003 Seasonal dynamics of benthic O2

uptake in a semienclosed bay Importance of diffusion and faunal activity Limnol Oceanogr 481265-1276

Hall P O J and R C Aller 1992 Rapid small-volume flow-injection analysis for yenCO2 and NH4

in marine and freshwaters Limnol Oceanogr 37 1113-1118Heilskov A C M Alperin and M Holmer 2006 Benthic fauna bio-irrigation effects on nutrient

regeneration in fish farm sediments J Exp Mar Biol Ecol 339 204-225Hoehler T M M J Alperin D B Albert and C S Martens 1994 Field and laboratory studies of

methane oxidation in an anoxic marine sediment - evidence for a methanogen-sulfate reducerconsortium Global Biogeochem Cy 8 451-463

Hoehler T M C B Albert M J Alperin and C S Martens 1999 Acetogenesis from CO2 in ananoxic marine sediment Limnol Oceanogr 44 662-667

Jackson D R and M D Richardson 2001 Seasonal temperature gradients within a sandy seafloorimplications for acoustic propagation and scattering in Acoustical Oceanography Proceedings ofthe Institute of Acoustics T G Leighton G J Heald H D Griffiths and G Griffiths eds 23361-368

Jensen J B and T Laier 2003 Cruise Report-MS Line Cruise to the Aringrhus Bay Geological Surveyof Denmark and Greenland Report 200396

Jin Q and C M Bethke 2005 Predicting the rate of microbial respiration in geochemicalenvironments Geochim Cosmochim Acta 69 1133-1143

Joslashrgensen B B 1978 A comparison of methods for the quantification of bacterial sulfate reductionin coastal marine sediments I Measurement with radiolabel techniques Geomicrobiol J 111-27

Klump J V and C S Martens 1989 The seasonality of nutrient regeneration in an organic-richcoastal sediment kinetic modeling of changing pore-water nutrient and sulfate distributionsLimnol Oceanogr 34 559-577

Koretsky C M P Van Cappellen T J DiChristina J E Kostka K L Lowe C M Moore A NRoychoudhury and E Viollier 2005 Salt marsh pore water geochemistry does not correlate withmicrobial community structure Estuar Coast Shelf Sci 62 233-251

Laier T and J B Jensen 2007 Shallow gas depth-contour map of the Skagerrak-western Baltic Searegion Geo-Mar Lett 27 127-141

Lasaga A C and H D Holland 1976 Mathematical aspects of non-steady-state diagenesisGeochim Cosmochim Acta 40 257-266

Martens C S D B Albert and M J Alperin 1998 Biogeochemical processes controlling methane


in gassy coastal sediments - Part 1 A model coupling organic matter flux to gas productionoxidation and transport Cont Shelf Res 18 1741-1770

Martens C S and R A Berner 1977 Interstitial water chemistry of anoxic Long Island Soundsediments 1 Dissolved gases Limnol Oceanogr 22 10-25

Matisoff G 1980 Time dependent transport in Chesapeake Bay sediments Part 1 Temperature andchloride Am J Sci 280 1-25

Meile C P Berg P Van Cappellen and K Tuncay 2005 Solute-specific pore water irrigationImplications for chemical cycling in early diagenesis J Mar Res 64 601-621

Meysman F J R O S Galaktionov B Gribsholt and J J Middelburg 2006 Bioirrigation inpermeable sediments Advective pore-water transport induced by burrow ventilation LimnolOceanogr 51 142-156

Mogollon J I LrsquoHeureux A Dale P Regnier 2008 Methane gas-phase dynamics in marinesediments a model study Am J Sci (submitted)

Moodley L J J Middelburg K Soetaert H T S Boschker P M Herman and C H R Heip2005 Similar rapid response to phytodetritus deposition in shallow and deep-sea sediments JMar Res 63 457-469

Nauhaus K T Treude A Boetius and M Kruger 2005 Environmental regulation of the anaerobicoxidation of methane a comparison of ANME-I and ANME-II communities Environ Microbiol7 98-106

Nittrouer C A G R Lopez D Wright S J Bentley A F DrsquoAndrea C T Friedrichs N I Craigand C K Sommerfield 1998 Oceanographic processes and the preservation of sedimentarystructure in Eckernforde Bay Baltic Sea Cont Shelf Res 18 1689-1714

Reeburgh W S 1996 ldquoSoft spotsrdquo in the global methane budget in Microbial Growth on C1Compounds M E Lidstrom and F R Tabita eds Kluwer Academic Publishers 334-342

Schluter M E Sauter H P Hansen and E Suess 2000 Seasonal variations of bioirrigation incoastal sediments modelling of field data Geochim Cosmochim Acta 64 821-834

Schulz H D 2000 Conceptual models and computer models in Marine Geochemistry H DSchulz and M Zabel eds Springer-Verlag Berlin 417-442

Sills G C and S J Wheeler 1992 The significance of gas for offshore operations Cont Shelf Res12 1239-1250

Soetaert K P M J Herman and J J Middelburg 1996 Dynamic response of deep-sea sedimentsto seasonal variations A model Limnol Oceanogr 41 1651-1668

Thamdrup B H Fossing and B B Joslashrgensen 1994 Manganese iron and sulfur cycling in a coastalmarine sediment Aarhus Bay Denmark Geochim Cosmochim Acta 58 5115-5129

Treude T M Kruger A Boetius and B B Joslashrgensen 2005 Environmental control on anaerobicoxidation of methane in the gassy sediments of Eckernforde Bay (German Baltic) LimnolOceanogr 50 1771-1786

Weston N B and S B Joye 2005 Temperature-driven decoupling of key phases of organic matterdegradation in marine sediments Proc Nat Acad Sci USA 102 17036-1740

Westrich J T and R A Berner 1984 The role of sedimentary organic matter in bacterial sulfatereduction the G-model tested Limnol Oceanogr 29 236-249

1988 The effect of temperature on rates of sulfate reduction in marine sediments Geomicro-biol J 6 99-117

Woodside W and J H Messmer 1961 Thermal conductivity of porous media I Unconsolidatedsands J Appl Phys 32 1688-1699

Received 14 May 2007 revised 10 March 2008


1 Introduction

Several detailed experimental studies have shown that organic matter mineralizationrates and microbial activity in both nearshore (eg Westrich and Berner 1988 Klump andMartens 1989) and deep-sea sedimentary environments (eg Soetaert et al 1996Moodley et al 2005) can be influenced by seasonal changes in temperature andorparticulate organic carbon (POC) flux to the sea floor Such seasonal variability at thesediment-water interface leads to concentration gradients of the primary oxidants of POCmineralization (eg O2 NO3

- Mn(IV) Fe(III) SO42-) which are not constant with time (Crill

and Martens 1987 Glud et al 2003 Koretsky et al 2005 Treude et al 2005) Themagnitude of this seasonal oscillation depends on the relative size of the perturbation at thesystem boundaries the rates of transport and reaction and thus on the quality of thesubstrate (Treude et al 2005 Burdige 2006) Additional complexities can be introducedby the substrate uptake response to temperature which is not necessarily the same for theentire microbial community (Weston and Joye 2005) Consequently modeling approacheshave proved useful to elucidate the seasonal variability observed in the redox biogeochem-istry of sediments (Klump and Martens 1989 Alperin et al 1994)

Aarhus Bay is a shallow embayment on the eastern Danish coast characterized by arelatively small yet notable seasonal change in the sediment depth distribution of oxidizedand reduced metabolites (eg Fe2 NH4

H2S) (Thamdrup et al 1994 Fossing et al2004) The quantitative significance of these seasonal changes for the sulfate reducing andmethanogenic zones has not yet been addressed although investigations elsewhere haverevealed seasonal variability resulting from significant changes in redox rates directly orindirectly coupled to organic matter decomposition (Crill and Martens 1987 Klump andMartens 1989) Sediment cores collected in Aarhus Bay and analyzed during theMETROL project (wwwmetrolorg) revealed that the subsurface sediments are methane-rich with a well-defined sulfate-methane transition zone (SMTZ) where sulfate andmethane simultaneously coexist In this SMTZ methane is oxidized anaerobically bymicroorganisms using sulfate as the terminal electron acceptor (Hoehler et al 1994Boetius et al 2000) Although anaerobic oxidation of methane (AOM) is a sluggishprocess it constitutes a globally effective sink against methane escape from marinesediments to the ocean and atmosphere (Reeburgh 1996) AOM is particularly relevant inthe sediments of Aarhus Bay because super-saturation of the pore water leads to theformation of methane bubbles which are detectable by ship-board seismic-acousticprofiling techniques (Laier and Jensen 2007) An investigation into the dynamics ofmethane and AOM over a seasonal cycle in an organic-rich nearshore environment such asAarhus Bay will thus provide additional constraints on the environmental factors regulat-ing the efficiency of the subsurface methane barrier

In this study a reaction-transport model (RTM) is applied to data from Aarhus Baysediments to investigate the role of seasonal bottom water temperature on substrateturnover rates with particular reference to sulfate reduction coupled to AOM and theSMTZ depth For the sake of completeness the variability in POC depositional flux is also





















SR

SO4

224







b Model set-up





(Eq 2c)

13CS

t

x 13DS DbCS

x 13vCS

x 13CS0 CS)13R (2a)

1 13CP

t

x 1 13Db

CP

x 1 13vCP

x 1 13R (2b)

13CH4g

t

x 13DCH4g DbCH4g

x 13vCH4g

x 13CH4g0 CH4g 13R

(2c)








min3 max




1frasl12 HCO3(aq)

1783 198 483 75



1frasl2 H2O(1)

9093 1010 5153 985



1frasl4 HCO3(aq)

3393 378 763 146



3frasl8 H2O(1)



23 3 03 1


1frasl8 H(aq)

203 24 763 178


1frasl8 H(aq) 3




1frasl8 H(aq)

243 27 53 11








(M1M5) Units






AOM15 103 M


10 107 M


10 103 M


10 103 M





























Baseline valuea

UnitM1 M5


temperature28115 K





0006 W cm1 K1


0025 W cm1 K1




4184 J g1 K1


0300 J g1 K1


18d 20d y1


140 150 cm1


10 cm1


12e cm2 y1

DSO42




LMW-DOC30g cm2 y1


DH2


DCH4


283f cm2 y1

DCH4(g)





bubbles300h 100h cm


Table 3 (Continued)


Baseline valuea

UnitM1 M5





(Eq 13)65 K


058 y


1 y

C0SO42 Measured SO4


22000 M


2000 M


5 M


20 M


01 nM


at x 010 M


at x 000




0 middot exp1 x

21 exp1 x

2






DS DS

0

1 ln 1321 T 27315 (3)




R1 j

fTkhyjPOCj (4)




dED

dt

i

fTvmaxiFKiFTi (6)

FKi ED

KEDi ED EA

KEAi EA (7)



RT (8)









CH4g 0(11)




CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions























































































SR

SO4

224







b Model set-up





(Eq 2c)

13CS

t

x 13DS DbCS

x 13vCS

x 13CS0 CS)13R (2a)

1 13CP

t

x 1 13Db

CP

x 1 13vCP

x 1 13R (2b)

13CH4g

t

x 13DCH4g DbCH4g

x 13vCH4g

x 13CH4g0 CH4g 13R

(2c)








min3 max




1frasl12 HCO3(aq)

1783 198 483 75



1frasl2 H2O(1)

9093 1010 5153 985



1frasl4 HCO3(aq)

3393 378 763 146



3frasl8 H2O(1)



23 3 03 1


1frasl8 H(aq)

203 24 763 178


1frasl8 H(aq) 3




1frasl8 H(aq)

243 27 53 11








(M1M5) Units






AOM15 103 M


10 107 M


10 103 M


10 103 M





























Baseline valuea

UnitM1 M5


temperature28115 K





0006 W cm1 K1


0025 W cm1 K1




4184 J g1 K1


0300 J g1 K1


18d 20d y1


140 150 cm1


10 cm1


12e cm2 y1

DSO42




LMW-DOC30g cm2 y1


DH2


DCH4


283f cm2 y1

DCH4(g)





bubbles300h 100h cm


Table 3 (Continued)


Baseline valuea

UnitM1 M5





(Eq 13)65 K


058 y


1 y

C0SO42 Measured SO4


22000 M


2000 M


5 M


20 M


01 nM


at x 010 M


at x 000




0 middot exp1 x

21 exp1 x

2






DS DS

0

1 ln 1321 T 27315 (3)




R1 j

fTkhyjPOCj (4)




dED

dt

i

fTvmaxiFKiFTi (6)

FKi ED

KEDi ED EA

KEAi EA (7)



RT (8)









CH4g 0(11)




CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions














































































SR

SO4

224







b Model set-up





(Eq 2c)

13CS

t

x 13DS DbCS

x 13vCS

x 13CS0 CS)13R (2a)

1 13CP

t

x 1 13Db

CP

x 1 13vCP

x 1 13R (2b)

13CH4g

t

x 13DCH4g DbCH4g

x 13vCH4g

x 13CH4g0 CH4g 13R

(2c)








min3 max




1frasl12 HCO3(aq)

1783 198 483 75



1frasl2 H2O(1)

9093 1010 5153 985



1frasl4 HCO3(aq)

3393 378 763 146



3frasl8 H2O(1)



23 3 03 1


1frasl8 H(aq)

203 24 763 178


1frasl8 H(aq) 3




1frasl8 H(aq)

243 27 53 11








(M1M5) Units






AOM15 103 M


10 107 M


10 103 M


10 103 M





























Baseline valuea

UnitM1 M5


temperature28115 K





0006 W cm1 K1


0025 W cm1 K1




4184 J g1 K1


0300 J g1 K1


18d 20d y1


140 150 cm1


10 cm1


12e cm2 y1

DSO42




LMW-DOC30g cm2 y1


DH2


DCH4


283f cm2 y1

DCH4(g)





bubbles300h 100h cm


Table 3 (Continued)


Baseline valuea

UnitM1 M5





(Eq 13)65 K


058 y


1 y

C0SO42 Measured SO4


22000 M


2000 M


5 M


20 M


01 nM


at x 010 M


at x 000




0 middot exp1 x

21 exp1 x

2






DS DS

0

1 ln 1321 T 27315 (3)




R1 j

fTkhyjPOCj (4)




dED

dt

i

fTvmaxiFKiFTi (6)

FKi ED

KEDi ED EA

KEAi EA (7)



RT (8)









CH4g 0(11)




CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions






































































b Model set-up





(Eq 2c)

13CS

t

x 13DS DbCS

x 13vCS

x 13CS0 CS)13R (2a)

1 13CP

t

x 1 13Db

CP

x 1 13vCP

x 1 13R (2b)

13CH4g

t

x 13DCH4g DbCH4g

x 13vCH4g

x 13CH4g0 CH4g 13R

(2c)








min3 max




1frasl12 HCO3(aq)

1783 198 483 75



1frasl2 H2O(1)

9093 1010 5153 985



1frasl4 HCO3(aq)

3393 378 763 146



3frasl8 H2O(1)



23 3 03 1


1frasl8 H(aq)

203 24 763 178


1frasl8 H(aq) 3




1frasl8 H(aq)

243 27 53 11








(M1M5) Units






AOM15 103 M


10 107 M


10 103 M


10 103 M





























Baseline valuea

UnitM1 M5


temperature28115 K





0006 W cm1 K1


0025 W cm1 K1




4184 J g1 K1


0300 J g1 K1


18d 20d y1


140 150 cm1


10 cm1


12e cm2 y1

DSO42




LMW-DOC30g cm2 y1


DH2


DCH4


283f cm2 y1

DCH4(g)





bubbles300h 100h cm


Table 3 (Continued)


Baseline valuea

UnitM1 M5





(Eq 13)65 K


058 y


1 y

C0SO42 Measured SO4


22000 M


2000 M


5 M


20 M


01 nM


at x 010 M


at x 000




0 middot exp1 x

21 exp1 x

2






DS DS

0

1 ln 1321 T 27315 (3)




R1 j

fTkhyjPOCj (4)




dED

dt

i

fTvmaxiFKiFTi (6)

FKi ED

KEDi ED EA

KEAi EA (7)



RT (8)









CH4g 0(11)




CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions








































































min3 max




1frasl12 HCO3(aq)

1783 198 483 75



1frasl2 H2O(1)

9093 1010 5153 985



1frasl4 HCO3(aq)

3393 378 763 146



3frasl8 H2O(1)



23 3 03 1


1frasl8 H(aq)

203 24 763 178


1frasl8 H(aq) 3




1frasl8 H(aq)

243 27 53 11








(M1M5) Units






AOM15 103 M


10 107 M


10 103 M


10 103 M





























Baseline valuea

UnitM1 M5


temperature28115 K





0006 W cm1 K1


0025 W cm1 K1




4184 J g1 K1


0300 J g1 K1


18d 20d y1


140 150 cm1


10 cm1


12e cm2 y1

DSO42




LMW-DOC30g cm2 y1


DH2


DCH4


283f cm2 y1

DCH4(g)





bubbles300h 100h cm


Table 3 (Continued)


Baseline valuea

UnitM1 M5





(Eq 13)65 K


058 y


1 y

C0SO42 Measured SO4


22000 M


2000 M


5 M


20 M


01 nM


at x 010 M


at x 000




0 middot exp1 x

21 exp1 x

2






DS DS

0

1 ln 1321 T 27315 (3)




R1 j

fTkhyjPOCj (4)




dED

dt

i

fTvmaxiFKiFTi (6)

FKi ED

KEDi ED EA

KEAi EA (7)



RT (8)









CH4g 0(11)




CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions






































































(M1M5) Units






AOM15 103 M


10 107 M


10 103 M


10 103 M





























Baseline valuea

UnitM1 M5


temperature28115 K





0006 W cm1 K1


0025 W cm1 K1




4184 J g1 K1


0300 J g1 K1


18d 20d y1


140 150 cm1


10 cm1


12e cm2 y1

DSO42




LMW-DOC30g cm2 y1


DH2


DCH4


283f cm2 y1

DCH4(g)





bubbles300h 100h cm


Table 3 (Continued)


Baseline valuea

UnitM1 M5





(Eq 13)65 K


058 y


1 y

C0SO42 Measured SO4


22000 M


2000 M


5 M


20 M


01 nM


at x 010 M


at x 000




0 middot exp1 x

21 exp1 x

2






DS DS

0

1 ln 1321 T 27315 (3)




R1 j

fTkhyjPOCj (4)




dED

dt

i

fTvmaxiFKiFTi (6)

FKi ED

KEDi ED EA

KEAi EA (7)



RT (8)









CH4g 0(11)




CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions






































































Baseline valuea

UnitM1 M5


temperature28115 K





0006 W cm1 K1


0025 W cm1 K1




4184 J g1 K1


0300 J g1 K1


18d 20d y1


140 150 cm1


10 cm1


12e cm2 y1

DSO42




LMW-DOC30g cm2 y1


DH2


DCH4


283f cm2 y1

DCH4(g)





bubbles300h 100h cm


Table 3 (Continued)


Baseline valuea

UnitM1 M5





(Eq 13)65 K


058 y


1 y

C0SO42 Measured SO4


22000 M


2000 M


5 M


20 M


01 nM


at x 010 M


at x 000




0 middot exp1 x

21 exp1 x

2






DS DS

0

1 ln 1321 T 27315 (3)




R1 j

fTkhyjPOCj (4)




dED

dt

i

fTvmaxiFKiFTi (6)

FKi ED

KEDi ED EA

KEAi EA (7)



RT (8)









CH4g 0(11)




CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions




































































Table 3 (Continued)


Baseline valuea

UnitM1 M5





(Eq 13)65 K


058 y


1 y

C0SO42 Measured SO4


22000 M


2000 M


5 M


20 M


01 nM


at x 010 M


at x 000




0 middot exp1 x

21 exp1 x

2






DS DS

0

1 ln 1321 T 27315 (3)




R1 j

fTkhyjPOCj (4)




dED

dt

i

fTvmaxiFKiFTi (6)

FKi ED

KEDi ED EA

KEAi EA (7)



RT (8)









CH4g 0(11)




CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions






































































DS DS

0

1 ln 1321 T 27315 (3)




R1 j

fTkhyjPOCj (4)




dED

dt

i

fTvmaxiFKiFTi (6)

FKi ED

KEDi ED EA

KEAi EA (7)



RT (8)









CH4g 0(11)




CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions





































































RT (8)









CH4g 0(11)




CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions






































































CH4 14388 107STP 4412 105TP 46842 105SP 4129 109ST

143465 102P 16027 106T 12676 106S 49581 104 (12)






TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions





































































TSWI Tav A0 sin 2t

(13)


T

t DT

2T

x2 (14)


DT ksw13 kds

113sw13 ds1 13csw13 cds1131 (15)



FSWI j

FPOCj1 sin 2t

(16)












0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions









































































0 10 20 30

SO42-

(mM)

200

100

0

700

Dep

th (

cm)

(a)

SO42-

CH4(aq)CH4(g)CH4

M1

0001 01 10 1000


(c)

fromPOCLAB

M1

0 10 20 30 40

DIC(mM)

(d)

M1

0 2 4 6

ΣPOC()

(e)

M1

0 2 4 30 60


(b)

SRAOM

M1

0 2 4 6 8 10 CH4(aq) CH4 (mM)

200

100

0

700

Dep

th (

cm)

0 2 4CH4(g) ()

(f)

M5

(i)

dot

M5

(j)

dot

M5

0 10 20 30 40AOM SR

(nmol cm-3 d-1)

(g)

M5

dot

0001 001 01 1 10 100 1000

(h)

fromPOCLAB

fromPOCMID

M5

dot
































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions
































































































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions


















































































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions











































































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions




































































Month in 2004

275

280

285

290

TS

WI (

K)

(a)


275 280 285 290TSWI (K)

700

600

500

400

300

200

100

0D

epth

(cm

)

ZSMTZ M1

ZSMTZ M5

2 3 1 4 12 5 11 6 10 7 9 8

(b)

275

280

285

290

TS

MT

Z (

K)

janfeb

marapr jun

jul

aug

octnovdec

may

sep

M1 (c)

275 280 285 290TSWI (K)

275

280

285

290

TS

MT

Z (

K)

jan

feb

mar

apr

jun

jul

augoct

nov

dec

may

sep

M5 (d)















0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions
















































































0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions





































































0 5 10 700 800 900


400

350

300

250

200

150

100

50

0

Dep

th (

cm)

(a)

M1

due to CH4(g)

due toSR amp AOM

due to SR

SO42-

CH4(aq)

0 01 02 20 40 60


400

350

300

250

200

150

100

50

0(b)

M1

SR

AOM

0 400 800 1200

200

150

100

50

0

Dep

th (

cm)

(c)

M5

due to CH4(g)

due to SR amp AOM

due to SR

SO42-

CH4(aq)

0 4 8 12 16 20

200

150

100

50

0(d)

M5

SR

AOM




05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions




































































05

06

07

08

09

AO

M (

nmol

cm

-3 d

-1)

jan

feb

marapr

jun

jul

aug

oct

novdec

may

sep

M1(a)

275 280 285 29014

16

18

20

22

24f(T)nov

aug

may

275 280 285 2900124

0126

0128apr

FK

dec

jul

sep

275 280 285 29000012

00013

00014

00015

00016

apr

FT

dec

aug

275 280 285 290TSMTZ (K)

0

5

10

15

20

AO

M (

nmol

cm

-3 d

-1)

janfeb

mar

apr

jun

julaug

oct

nov

dec

may

sep

M5(b)

275 280 285 29000

10

20

30

40

50

mar

f(T)

dec

jul

sep

275 280 285 29003

04

05

aprFK

decjul

sep

275 280 285 2900004

0005

0006

0007

apr

FT

dec

junaug








275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions









































































275 280 285 290TSWI (K)

10

11

12

13

ΣAO

M (

nmol

cm

-2 d

-1)

jan

feb

mar

aprjun

jul

aug

octnov

dec

may

sep

M1 (a)

Baseline rate

275 280 285 290TSWI (K)

40

60

80

100

120

140

160

jan

febmar

apr

jun

jul aug

oct

nov

dec

may

sep

M5 (b)

Baseline rate










0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions











































































0 035 04

SO42- CH4 (mM)

210

209

208

Dep

th (

cm)

(a)

M1

SO42-

CH4(aq)

may jundec jan

0 1 2 3 4 5 6

SO42- CH4 (mM)

80

70

60

50(b)

M5

SO42-

CH4(aq)

apr maysep oct
















2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions















































































2-














M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions













































































M1 221 40 221 18 221 2 221 34M5 63 8 63 5 63 10 63 9



4 Conclusions





































































4 Conclusions






































































































































































































Documents

Seasonal dynamics of the depth and rate of anaerobic ...eprints.uni-kiel.de/235/1/s5.pdf · Seasonal dynamics of the depth and rate of anaerobic oxidation of methane in Aarhus Bay